2008
DOI: 10.3846/1392-8619.2008.14.388-401
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Mathematical Modelling of Forecasting the Results of Knowledge Testing / Žinių Tikrinimo Rezultatų Prognozės Matematinis Modeliavimas

Abstract: Abstract. In this paper a mathematical model for obtaining probability distribution of the knowledge testing results is proposed. Differences and similarities of this model and Item Response Theory (IRT) logistic model are discussed. Probability distributions of 10 items test results for low, middle and high ability populations selecting characteristic functions of the various difficulty items combinations are obtained. Entropy function values for these items combinations are counted. These results enable to f… Show more

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Cited by 6 publications
(5 citation statements)
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“…Segments of linear functions 1 ( ) f p are represented by trapezium or triangle depending on the parameter values (Krylovas, Kosareva 2008a). Beta distribution probability density function initially satisfies features (9) and (10).…”
Section: Mathematical Model Of Experimentsmentioning
confidence: 99%
“…Segments of linear functions 1 ( ) f p are represented by trapezium or triangle depending on the parameter values (Krylovas, Kosareva 2008a). Beta distribution probability density function initially satisfies features (9) and (10).…”
Section: Mathematical Model Of Experimentsmentioning
confidence: 99%
“…Constant and dynamic development of those techniques can be observed (Kapliński 2008b, c). Numerous examples of the development of these techniques are published, for example: Jurkevičius and Laukaitis 2007; Kapliński and Zavadskas 1997;Krylovas and Kosareva 2008;Mickaityte et al 2007;Nassar and Casavant 2008;Lee and Egbu 2007;Turskis et al 2006;Turskis 2008;Popov et al 2006;Schafer and Sędziwy 2001;Scheer et al 2007. Various other aspects was analysed by: Khamkanya and Sloan 2008; Mitkus and Trinkuniene 2008;Rutkauskas 2008;Rutkauskas et al 2008;Samuelson 2008;Šelih 2007;Skorupka 2005;Zavadskas et al 2008a. Other considerations in the context of economy are presented by: Ginevičius and Podvezko 2008; Kaganova et al 2008;Kaklauskas et al 2007;Kapliński 1985Kapliński , 1993Kapliński , 2001Mickaityte et al 2008;Mitkus and Sostak 2008.…”
Section: Changes In Approach Towards Information Technologymentioning
confidence: 99%
“…Fuzzy set (Zadeh 1965;Peldschus and Zavadskas 2005;Hui et al 2009;Krylovas and Kosareva 2008) is a core concept in this article. A fuzzy set is a generalized version of a classical set (or a crisp set).…”
Section: Methodsmentioning
confidence: 99%